| Sequence variants in SLC16A11 are a common risk factor for type 2 diabetes in Mexico AL Williams, SBR Jacobs, H Moreno-Macías, A Huerta-Chagoya, ... Nature 506 (7486), 97-101, 2014 | 562 | 2014 |
| Loss-of-function mutations in SLC30A8 protect against type 2 diabetes J Flannick, G Thorleifsson, NL Beer, SBR Jacobs, N Grarup, NP Burtt, ... Nature genetics 46 (4), 357-363, 2014 | 545 | 2014 |
| Rare variants in PPARG with decreased activity in adipocyte differentiation are associated with increased risk of type 2 diabetes AR Majithia, J Flannick, P Shahinian, M Guo, MA Bray, P Fontanillas, ... Proceedings of the National Academy of Sciences 111 (36), 13127-13132, 2014 | 178 | 2014 |
| Impact of laparoscopic radical hysterectomy on survival outcome in patients with FIGO stage IB cervical cancer: a matching study of two institutional hospitals in Korea SI Kim, M Lee, S Lee, DH Suh, HS Kim, K Kim, HH Chung, JH No, JW Kim, ... Gynecologic Oncology 155 (1), 75-82, 2019 | 85 | 2019 |
| Pathway-based approach using hierarchical components of collapsed rare variants S Lee, S Choi, YJ Kim, BJ Kim, T2d-Genes Consortium, H Hwang, T Park Bioinformatics 32 (17), i586-i594, 2016 | 46 | 2016 |
| Evaluating the contribution of rare variants to type 2 diabetes and related traits using pedigrees G Jun, A Manning, M Almeida, M Zawistowski, AR Wood, TM Teslovich, ... Proceedings of the National Academy of Sciences 115 (2), 379-384, 2018 | 41 | 2018 |
| FARVAT: a family-based rare variant association test S Choi, S Lee, S Cichon, MM Nöthen, C Lange, T Park, S Won Bioinformatics 30 (22), 3197-3205, 2014 | 37 | 2014 |
| ONETOOL for the analysis of family-based big data YE Song, S Lee, K Park, RC Elston, HJ Yang, S Won Bioinformatics 34 (16), 2851-2853, 2018 | 34 | 2018 |
| Prediction of response to sorafenib in hepatocellular carcinoma: a putative marker panel by multiple reaction monitoring-mass spectrometry (MRM-MS) H Kim, SJ Yu, I Yeo, YY Cho, DH Lee, Y Cho, EJ Cho, JH Lee, YJ Kim, ... Molecular & Cellular Proteomics 16 (7), 1312-1323, 2017 | 34 | 2017 |
| Dietary wolfberry extract modifies oxidative stress by controlling the expression of inflammatory mRNAs in overweight and hypercholesterolemic subjects: a randomized, double … YJ Lee, Y Ahn, O Kwon, MY Lee, CH Lee, S Lee, T Park, SW Kwon, ... Journal of agricultural and food chemistry 65 (2), 309-316, 2017 | 33 | 2017 |
| Proteomic discovery of biomarkers to predict prognosis of high-grade serous ovarian carcinoma SI Kim, M Jung, K Dan, S Lee, C Lee, HS Kim, HH Chung, JW Kim, ... Cancers 12 (4), 790, 2020 | 25 | 2020 |
| On the estimation of heritability with family‐based and population‐based samples Y Kim, Y Lee, S Lee, NH Kim, J Lim, YJ Kim, JH Oh, H Min, M Lee, HJ Seo, ... BioMed Research International 2015 (1), 671349, 2015 | 21 | 2015 |
| Development of web-based nomograms to predict treatment response and prognosis of epithelial ovarian cancer SI Kim, M Song, S Hwangbo, S Lee, U Cho, JH Kim, M Lee, HS Kim, ... Cancer Research and Treatment: Official Journal of Korean Cancer Association …, 2019 | 19 | 2019 |
| Hierarchical structural component modeling of microRNA-mRNA integration analysis Y Kim, S Lee, S Choi, JY Jang, T Park BMC bioinformatics 19, 25-34, 2018 | 19 | 2018 |
| A novel fuzzy set based multifactor dimensionality reduction method for detecting gene–gene interaction HY Jung, S Leem, S Lee, T Park Computational biology and chemistry 65, 193-202, 2016 | 18 | 2016 |
| Adjusting heterogeneous ascertainment bias for genetic association analysis with extended families S Park, S Lee, Y Lee, C Herold, B Hooli, K Mullin, T Park, C Park, ... BMC medical genetics 16, 1-12, 2015 | 15 | 2015 |
| Risk prediction for malignant intraductal papillary mucinous neoplasm of the pancreas: logistic regression versus machine learning JS Kang, C Lee, W Song, W Choo, S Lee, S Lee, Y Han, C Bassi, R Salvia, ... Scientific reports 10 (1), 20140, 2020 | 14 | 2020 |
| HisCoM-GGI: hierarchical structural component analysis of gene–gene interactions S Choi, S Lee, Y Kim, H Hwang, T Park Journal of bioinformatics and computational biology 16 (06), 1840026, 2018 | 14 | 2018 |
| Family-based association analysis: a fast and efficient method of multivariate association analysis with multiple variants S Won, W Kim, S Lee, Y Lee, J Sung, T Park BMC bioinformatics 16, 1-14, 2015 | 14 | 2015 |
| WISARD: workbench for integrated superfast association studies for related datasets S Lee, S Choi, D Qiao, M Cho, EK Silverman, T Park, S Won BMC Medical Genomics 11, 33-44, 2018 | 13 | 2018 |
Taesung ParkProfessor of Statistics, Seoul National University在 stats.snu.ac.kr 的电子邮件经过验证
